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IP Online First, published on February 14, 2013 as 10.1136/injuryprev-2012-040561
Original article
Comparing the effects of infrastructure on bicycling
injury at intersections and non-intersections using
a case–crossover design
M Anne Harris,1 Conor C O Reynolds,2,3 Meghan Winters,4 Peter A Cripton,5
Hui Shen,6 Mary L Chipman,7 Michael D Cusimano,8,9 Shelina Babul,10
Jeffrey R Brubacher,11 Steven M Friedman,12,13 Garth Hunte,11 Melody Monro,6
Lee Vernich,7 Kay Teschke6
▸ Additional material is
published online only. To view
please visit the journal online
(http://dx.doi.org/10.1136/
injuryprev-2012-040561).
For numbered affiliations see
end of article
Correspondence to
Dr M Anne Harris, School of
Occupational and Public
Health, Ryerson University,
Toronto, ON M5B 2K3,
Canada;
[email protected]
Received 17 July 2012
Revised 4 December 2012
Accepted 14 December 2012
ABSTRACT
Background This study examined the impact of
transportation infrastructure at intersection and nonintersection locations on bicycling injury risk.
Methods In Vancouver and Toronto, we studied adult
cyclists who were injured and treated at a hospital
emergency department. A case–crossover design
compared the infrastructure of injury and control sites
within each injured bicyclist’s route. Intersection injury
sites (N=210) were compared to randomly selected
intersection control sites (N=272). Non-intersection
injury sites (N=478) were compared to randomly
selected non-intersection control sites (N=801).
Results At intersections, the types of routes meeting
and the intersection design influenced safety.
Intersections of two local streets (no demarcated traffic
lanes) had approximately one-fifth the risk (adjusted OR
0.19, 95% CI 0.05 to 0.66) of intersections of two
major streets (more than two traffic lanes). Motor vehicle
speeds less than 30 km/h also reduced risk (adjusted OR
0.52, 95% CI 0.29 to 0.92). Traffic circles (small
roundabouts) on local streets increased the risk of these
otherwise safe intersections (adjusted OR 7.98, 95% CI
1.79 to 35.6). At non-intersection locations, very low
risks were found for cycle tracks (bike lanes physically
separated from motor vehicle traffic; adjusted OR 0.05,
95% CI 0.01 to 0.59) and local streets with diverters
that reduce motor vehicle traffic (adjusted OR 0.04, 95%
CI 0.003 to 0.60). Downhill grades increased risks at
both intersections and non-intersections.
Conclusions These results provide guidance for
transportation planners and engineers: at local street
intersections, traditional stops are safer than traffic
circles, and at non-intersections, cycle tracks alongside
major streets and traffic diversion from local streets are
safer than no bicycle infrastructure.
INTRODUCTION
To cite: Harris MA,
Reynolds CCO, Winters M,
et al. Inj Prev Published
Online First: [ please include
Day Month Year]
doi:10.1136/injuryprev2012-040561
Despite many potential health benefits of cycling1–4
as an active transportation mode, safety concerns
deter people from cycling in North America.5 Injury
data from the USA suggest these concerns are valid:
Beck et al6 found that cyclists there were at greater
risk of both fatal and non-fatal injuries than motor
vehicle occupants. However, cycling injury risk
could be much lower, as shown by continental differences in cycling safety. Canadian and American
cyclists are two to six times more likely to be killed
while cycling than Danish or Dutch cyclists7 8 and
Harris
MA, et al. InjArticle
Prev 2013;0:1–8.
doi:10.1136/injuryprev-2012-040561
Copyright
author
(or their employer) 2013.
American cyclists are eight to 30 times more likely
to be seriously injured than cyclists in Germany,
Denmark and The Netherlands.9
Road infrastructure that separates motor vehicles
from bicycles is prevalent in the cycling countries of
northern Europe but not in North America, which
could explain some of the observed difference in
cycling safety.4 5 We reviewed the evidence on route
infrastructure and injury risk,6 and found evidence
that bicycle-specific infrastructure (eg, bike routes,
painted bike lanes and off-road bike paths) was associated with the lowest injury risks, that sidewalks
and multi-use trails were associated with higher
risks, and that major roads had higher risks than
minor or local roads. At intersections, roundabouts,
higher vehicle volumes and multiple vehicle and
turning lanes were associated with higher risks.
However, the evidence on infrastructure and injuries
remains sparse and faces challenges that have rendered conclusions difficult and often controversial.
Many studies have unclear route definitions, broad
route groupings and insufficient adjustment for
exposure to risk and confounders.
We conducted a case–crossover study in the
Canadian cities of Vancouver and Toronto10 to
examine the influence of infrastructure on injury risk,
while ensuring strict control for denominators (ie,
exposure to risk, cyclist traffic volume) and for personal and trip characteristics (eg, propensity for risktaking, time of day). The study design included two
main sets of analyses. The first set, reported elsewhere,11 compared injury sites to randomly selected
control sites of any type, and showed that bicyclespecific route infrastructure was associated with
decreased injury risk, providing more detailed
support to previous findings.12 13
This paper presents the second set of analyses. It
examines intersections and non-intersections separately to assess the distinct features of each, and to
determine if the impact of infrastructure differed at
these two location types.14 To do this, we used
control sites matched to injury sites based on intersection status.
METHODS
The study was conducted in the cities of Toronto
and Vancouver, Canada, where the proportions of
trips to work by bicycle were 1.7% and 3.7% in
2006, respectively, according the 2006 Canadian
Census. Toronto has a population of approximately
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Original article
2.5 million, an area of 630 km2, snowy winter weather and
warm summer weather, and Vancouver has a population of
approximately 0.6 million, an area of 115 km2, rainy winter
weather and mild summer weather. At the time of the study,
both cities had the cycling infrastructure most common in
North American cities, mainly local street bikeways, off-street
paths and painted bike lanes (∼400–500 km in each city). The
following were differences in cycling-related circumstances
between the cities: Toronto had streetcar tracks on many major
streets and Vancouver was subject to a helmet law for adults,
had traffic circles at some local street intersections, and had
cycle tracks alongside a few major or minor streets (see route
infrastructure definitions, table 1).
We conducted a case–crossover study,10 15 a design that uses
injured participants as their own controls, well suited to studies
of the effects of transient exposures (eg, varying infrastructure
along a cycling trip) on acute events (eg, injury). Comparisons
within individuals and trips are fully controlled for personal
factors (eg, age, sex, cycling experience) and trip characteristics
(eg, weather, bike type, safety equipment use).10 15 Our overall
design is described in detail elsewhere.10 11
The study population included injured cyclists aged 19 years
and over who were treated at emergency departments at study
hospitals in Vancouver (St Paul’s, Vancouver General) or
Toronto (St Michael’s, Toronto General, Toronto Western)
between 18 May 2008 and 30 November 2009. Canadian hospitals are publicly funded so those injured and seeking emergency treatment in the catchment areas (the cities’ urban cores)
are likely to present to one of the study hospitals. All study hospitals were university affiliated, and one regional tertiary trauma
centre was included in each city. Injured cyclists were identified
on intake as having been injured in a cycling crash. Hospital
research staff reviewed intake records at least weekly, then
relayed contact information to the study coordinators in their
respective city. Introductory letters were sent to all potential
participants, followed by a phone call from the study
coordinator to invite participation and screen for eligibility. Up
to 10 contact attempts per injured bicyclist were made over
3 months following the injuries. We excluded cyclists who were:
▸ Injured outside of Toronto or Vancouver or did not reside
in the study cities (the geographical areas were the postal
definition of the cities themselves, and did not include the
surrounding metropolitan municipalities).
▸ Unable to participate in an interview (fatally injured,
injured too seriously to communicate, could not speak
English, or unable to remember the trip).
▸ Injured while trick riding, racing, mountain biking, participating in a critical mass ride, or while on private property.
▸ Injured while riding a motorised bike (eg, electric scooter
or pedal-assisted e-bike), unicycle or tandem bike.
▸ Already enrolled in the study due to a previous injury.
The study design and recruitment protocol were evaluated
and approved by research ethics boards at the universities of
British Columbia and Toronto and each participating hospital.
Eligible participants were interviewed in person as soon after
the injury as possible to maximise recall. The structured questionnaire16 took 25–45 min to complete. The interviewers collected data on characteristics of the trip (eg, weather conditions,
time of day, clothing worn, helmet use, etc) and of the cyclist
(age, sex, education, income, cycling experience), although
these were not required as adjustment factors in the analysis due
to the crossover design. Characteristics of the injury and control
sites, described below, were also documented (eg, presence of
construction, where the cyclist was riding at the time—eg, on
the sidewalk or the street, which lane or side of street).
Participants traced their trip route on a city map (scale 1 :
31 250) and indicated the injury site. The interviewer used a map
wheel (Calculated Industries ScaleMaster 6020 Classic, Carson
City, Nevada, USA) to determine the trip distance. Control sites
on the same route were identified by multiplying a randomly generated proportion (MS Excel, Microsoft, Redmond, Washington,
USA) by the trip distance, then tracing the resulting distance
Table 1 Definitions of route types and bicycling infrastructure, and selected characteristics as observed at the randomly selected study control
sites
Route types
Major streets
Minor streets
Local streets
Separated
Bicycling infrastructure
Cycle track
Bike lane
Bike path
Multi-use path
Sharrows or shared lane
Traffic diverter on local streets
Traffic slowing device on local streets
Traffic circle
Paved city streets with more than two demarcated moving lanes of motor vehicle traffic, mainly arterials; median* motor vehicle
speed 40 km/h; median motor vehicle traffic 966/h, median cyclist traffic 36/h
Paved city streets with two demarcated moving lanes of motor vehicle traffic, mainly connectors; median motor vehicle speed
37 km/h; median motor vehicle traffic 576/h, median cyclist traffic 24/h
Paved city streets with no demarcated lanes for motor vehicle traffic; most were in residential areas; median motor vehicle speed
30 km/h; median motor vehicle traffic 48/h, median cyclist traffic 0/h
Routes that were physically separated from traffic, at least on segments between intersections; no motor vehicle traffic, median
cyclist traffic 24/h, median pedestrian traffic 12/h
Paved path meant for cyclist use alongside major or minor streets, separated by a physical barrier, for example, a curb or
bollards
Bicycle-only lane on a major or minor street, marked with solid or dotted lines on the street surface
Bicycle-only paved path meant for cyclist use away from streets, for example, in parks
Paved or unpaved path meant for non-motorised use by pedestrians, cyclists, skaters and others, either alongside city streets or
away from streets, for example, in parks
Section of a major or minor street with markings on the street surface indicating shared bike–high occupancy vehicle (HOV) lane,
shared bike–bus lane, or sharrows indicating bikes and motor vehicles share space
Median, diverter and any other treatment (at the nearest intersection) designed to prevent some or all motor vehicle traffic from
entering the street
Traffic circles or curb extensions (at the nearest intersection) and speed humps or bumps (within 100 m of the site); designed to
reduce motor vehicle speeds and, in the case of curb extensions, also facilitate pedestrian crossing
A small version (usually 6–8 m in diameter) of a roundabout implemented at intersections of two local streets (see also
figure 4); all traffic is required to travel around the central circular island to the right
*Median vehicle speeds and traffic counts as measured at the randomly selected control sites.
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Original article
along the route using the map wheel. One control site was deliberately matched to the intersection status of the injury site, by
adjusting it forward or back (even or odd random number,
respectively) along the route until it matched. The other control
site was selected in the same way, except without matching on
intersection status. These unmatched sites were used in the first
set of study analyses, reported earlier,11 but as some of them did
match the injury site on intersection status by chance alone, we
were able to include them as additional controls in this analysis
to augment statistical power.
Trained observers completed a site observation form17 developed for the study in consultation with transportation engineering personnel. The form was pretested for feasibility, detail and
clarity at 16 sites, revised, then tested for intra-observer reliability at 25 sites, reported elsewhere.11 The observers were blinded
to the injury or control status of the sites. Observations were
timed to match the time of day of the injury trip (weekday vs
weekend; morning rush, mid-day, afternoon rush, evening,
night). The observation form recorded information at the location of the cyclist at each site and considered the cyclist’s direction of travel. Observations included the characteristics of the
routes and intersecting streets, the presence of cycling infrastructure (eg, bike lanes, cycle tracks, signage), presence and type of
intersection (eg, two-way stop, four-way stop, stoplight, traffic
circle), streetcar tracks and street lighting. Measurements
included surface grade (measured using a Suunto PM-5 clinometer, Vantaa, Finland), distance visible along the direction of
travel (measured using a Rolatape Measure Master MM-12
trundle wheel, Watseka, Illinois, USA), counts of motor vehicle,
cyclist and/or pedestrian traffic volume in 5 min in both directions and average motor vehicle traffic speed (five vehicles measured at normal traffic speeds, ie, not as they were accelerating
from or decelerating to a stop, using a Bushnell Velocity Speed
Gun, Overland Park, Kansas, USA).
Separate analyses were performed to evaluate the effects of
infrastructure (table 1) in crashes occurring at intersections and
non-intersections. Conditional logistic regression with one or
two control sites per injury site was used to estimate associations
between injury and infrastructural characteristics. The dependent variable was binary (1=injury site or 0=control site), and
OR were calculated using the following model:
log½pij =ð1 pij Þ ¼ ai þ xij1 b1 þ xij2 b2 þ þ xijp b p ;
ð1Þ
where πij is the probability of injury for the ith subject and jth
site, given the covariates xij1, xij2, …, xijp. i=1, …, N; j=1, …,
ni. N is the number of subjects; ni=2 if there was one injury site
and one control site and ni=3 if there was one injury site and
two control sites; and p is the number of covariates.
Independent variables including route types and bicycling infrastructure were defined (table 1) with the help of city transportation
engineering personnel. Most infrastructure variables offered in the
models were the same for intersection and non-intersection analyses. For intersections, two additional design variables were
offered: the route types meeting at the intersections and the type
of intersection control. Initial analyses tested the effects of each
variable in simple bivariate models. Two final multiple logistic
regression models (one for intersections and one for nonintersections) were constructed using backwards selection, starting
by offering all variables of interest. The variable with the highest p
value (Wald test) was removed and the model refit with the
remaining variables until all variables were statistically significant
(p<0.05). Analyses were performed with SAS V.9.2.
RESULTS
Participants and trips
Of 2335 injured cyclists who were treated at a study emergency
department during the study period, 927 were ineligible, 741
were eligible and 690 agreed to participate (414 from
Vancouver and 276 from Toronto). There were 667 with
unknown eligibility, including 124 refusals and 543 not contacted (because of incorrect phone numbers or addresses, or no
response with repeated phone calls within 3 months).
Participants represented 93.1% of those confirmed to be eligible
and 66.5% of those estimated to be eligible (based on the proportion eligible among those contacted).11 Common reasons for
ineligibility were not being a resident of the study city or being
injured outside the city. A complete accounting of participation
is included as a supplemental figure in an earlier paper.11
Of the 690 participants, 211 were injured at intersections and
479 at non-intersection sites. No matched control site was
selected for one person injured at an intersection and one
injured at a non-intersection, so these cases were excluded from
the analyses. The 210 intersection injury sites were matched to
272 control sites (210 matched deliberately and 62 matched by
chance). The 478 non-intersection injury sites were matched to
801 control sites (478 deliberately and 323 by chance). This
matching process is illustrated in figure 1.
Figure 1 Process by which injury and control sites were matched based on whether injuries occurred at intersections or not in a case–crossover
study conducted in Vancouver and Toronto (Canada).
Harris MA, et al. Inj Prev 2013;0:1–8. doi:10.1136/injuryprev-2012-040561
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Injuries at intersections
Injuries at non-intersection locations
The unadjusted and adjusted associations of all variables that were
included in the final model of intersection characteristics and
bicycling injury are shown in figure 2. Compared to intersections
of two major streets, intersections of two local streets were associated with significantly lower odds of injury (adjusted OR 0.19,
95% CI 0.05 to 0.66). Intersection type was associated with injury,
with the highest risk noted for traffic circles, a relationship that
was strengthened and became significant after adjustment for
other variables (adjusted OR 7.98, 95% CI 1.79 to 35.6).
Compared to motor vehicle speeds of 31–50 km/h, speeds below
30 km/h were associated with lower cycling injury risk (adjusted
OR 0.52, 95% CI 0.29 to 0.92). Cycling in the direction opposite
to motor vehicle travel was associated with increased injury risk
(adjusted OR 7.8, 95% CI2.02 to 30.3), as were downhill grade
(adjusted OR 2.22, 95% CI 1.21 to 4.08) and high cycling traffic
(more than 75 cyclists/h, adjusted OR 3.04, 95% CI 1.17 to 7.93).
The variable ‘bike or pedestrian infrastructure’ (table 1) was not
associated with an increased or decreased injury risk at intersections and was therefore not included in this model. The unadjusted
and adjusted effects of all variables considered in intersection risk
modelling are available in supplementary table S1 (available online
only).
The unadjusted and adjusted associations of all variables that
were retained in the final model of non-intersection characteristics and bicycling injury are shown in figure 3. Bicycle-specific
infrastructure was associated with reduced injury risk in nonintersection locations. Cycle tracks ( physically separated lanes
alongside major streets) (adjusted OR 0.05, 95% CI 0.01 to
0.59) and local streets with diverters at the nearest intersection to
reduce motor vehicle traffic (adjusted OR 0.04, 95% CI 0.003 to
0.60) were especially protective. The presence of streetcar or
train tracks within a 5 m diameter of the site was associated with
increased injury risk (adjusted OR 4.15, 95% CI 2.31 to 7.45) as
was downhill grade (adjusted OR 2.05, 95% CI 1.48 to 2.85)
and the presence of construction at the site during the injury trip
(adjusted OR 2.67, 95% CI 1.70 to 4.19). Although it was not
statistically significant, we also found a suggestion of increased
risk with shared lanes or sharrows (adjusted OR 1.99, 95% CI
0.76 to 5.20). Results for all variables considered are available in
supplementary table S2 (available online only).
DISCUSSION
In this study, the types of routes meeting, the intersection configuration, the speed of vehicles, the amount of cycling traffic
Figure 2 Intersections: results of conditional logistic regression analyses of associations between infrastructural characteristics and bicycling injury
in a case–crossover study conducted in Vancouver and Toronto (Canada). Shown are the effects for single variables (left) and for all these variables
together in the final multiple regression model (right), with final variables selected via a backward selection (comparison of N=210 injury sites and
N=272 control sites, all at intersections). Closed circles represent the reference category for each variable.
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Figure 3 Non-intersections: results of conditional logistic regression analyses of associations between infrastructural characteristics and bicycling
injury in a case–crossover study conducted in Vancouver and Toronto (Canada). Shown are the effects for single variables (left) and for all these
variables together in the final multiple regression model (right), with final variables selected via a backward selection (comparison of N=478 injury
sites and N=801 control sites, all at non-intersection locations). Closed circles represent the reference category for each variable.
and the direction of cyclist travel were all related to injury risk
at intersections.
Intersections involving local streets or separated routes tended
to have the lowest risks, with local–local street intersections
having about one-fifth the risk of major–major street intersections. Low motor vehicle speeds were also protective. Average
observed speeds less than 30 km/h had about one-half the risk
of higher speeds at intersections. Speed limits of 30 km/h are
mandated on residential streets in northern European countries
where cycling is safer.9
Traffic circles were more hazardous than all other intersection
types (traffic lights, two-way stops, four-way stops and uncontrolled intersections). All traffic circles were in Vancouver, at intersections of two local streets (intersections that were otherwise
found to be very safe). In Vancouver, local street traffic circles are
small (approximately 6–8 m in diameter; figure 4) unlike major
street roundabouts common in Europe. Comparisons are difficult
because of the size difference, but other studies have shown that
large roundabouts (∼30 m in diameter) reduce injury risk for
motor vehicle occupants and this has fostered interest in this intersection design.18 19 Despite the reduced risk for motor vehicles at
roundabouts, studies of cyclists have found increased risks.20–22
Brüde and Larsson23 showed that roundabouts with radii greater
than 10 m were safer than smaller circles. Daniels et al21 and
Schoon and Van Minnen19 showed reductions in roundabout risks
for cyclists when there were lanes physically separated from motor
vehicles. The increased risk to cyclists associated with traffic circles
and roundabouts could relate to the large number of associated
‘conflict points’.24 In our study, the two main types of crashes at
traffic circles were with motor vehicles (n=8), because the cyclist
was not seen, or were single cyclist crashes (n=9), resulting from
interactions with the infrastructure (eg, hitting the curb, sliding on
the sharp turn).
We included a variable indicating whether the cyclist was travelling in the opposite direction to motor vehicles and found it
to increase risk at intersections significantly. While not an infrastructural variable, it can be related to infrastructure (eg,
Harris MA, et al. Inj Prev 2013;0:1–8. doi:10.1136/injuryprev-2012-040561
Figure 4 A typical traffic circle found in residential areas of
Vancouver, designed to calm motor vehicle traffic, but found to
increase risk at intersections of local streets in this study. (A)
Photograph as viewed from the perspective of an approaching cyclist.
(B) Design dimensions of traffic circle (derived from measurements
taken throughout the city). The dashed arrow shows the route a cyclist
is required to take when turning left.
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sidewalk riding) or forced by infrastructure (two-way cycle lanes
at one side of the street). At the time of the study, none of the
route infrastructure in Vancouver or Toronto mandated cycling
in the direction opposite to traffic. The wrong-way crashes in
this study were among cyclists entering the intersection from
sidewalks (n=10) or local streets (n=8; traffic lanes are not
demarcated and cyclists rode on the left instead of the right side
of the street). One other study found an increased risk of a
crash for cyclists riding on sidewalks when entering an intersection in the direction opposite to traffic flow.25
Intersections with high cycling traffic counts (more than 75/h)
were associated with increased injury risk. Most of these crashes
were with motor vehicles (n=51), not with other cyclists (n=1).
Many studies have found increased safety with increased trips
by bicycle.26 27 Most data about ‘safety in numbers’ is at the
macro level (ie, city or country level), whereas our analysis
examined the micro level (intersections). Two other recent
studies examined the impact of increased cyclist volume at intersections: one in Finland showed lower crash risk with increased
cyclist volume at a newly installed raised bicycle crossing;28 and
one in Montréal found injury risk increased at a lower rate than
cyclist volumes at signalised intersections.29 Our results may
thus not be generalisable.
At intersection locations, we found that any bike or pedestrian
infrastructure that the cyclist was riding on before entering the
intersection (eg, cycle tracks, bike lanes, sidewalks) was not significantly associated with injury risk. This is probably because, in
Vancouver and Toronto at the time of the study, this type of infrastructure was implemented along streets between intersections,
not through intersections themselves. Although many northern
European countries implement special features for cyclists at intersections, these were almost never observed in our study cities. We
could only measure the effects of infrastructure implemented at
the time of the study.
The benefits of cycling-specific infrastructure were apparent at
non-intersection locations. Our consistent finding11 that cycle
tracks decrease risk are similar to findings by Lusk et al12 in
Montréal. Other studies have also found decreased risks for
bicycle lanes30–34 or cycle tracks.19 Because previous research
has shown increased risks for separated facilities such as offstreet paths and sidewalks,31–33 35 36 some North American
transportation safety advocates argue against cycle tracks and
other bicycle-specific infrastructure.37 However, our results
support separation from motor vehicles for injury prevention.
Conversely, infrastructure that pairs cyclists with either motor
vehicles (shared lanes and sharrows) or pedestrians (multi-use
paths, sidewalks) offered no such protection. Shared lanes and
sidewalks were associated with increased odds of injury, albeit
not statistically significantly. Our findings highlight the importance of distinguishing bicycle-specific from mixed-use infrastructure in analyses of risk.
Similar to cycle tracks, local streets with diverters to reduce
motor vehicle traffic were found to have very low risk, probably
because they reduce motor vehicle volumes. Traffic slowing
devices (eg, traffic circles, curb extensions and speed bumps or
humps) are also considered ‘traffic calming’ measures and were
implemented to slow traffic on local streets, but were not found
to have a significant benefit. One study found that motor vehicles may speed up immediately after a traffic-slowing device.38
We found that streetcar tracks and construction were associated with increased risk of cycling injury, consistent with our
previous analysis.11 The construction finding suggests the need
for demarcated route detours to allow cyclists to avoid construction zones. Our finding that streetcar tracks are associated with
6
injury appears to be new to the empirical literature, although
these have long been thought hazardous by Toronto cyclists.36
Downhill grade was associated with increased risk at both
intersections and non-intersections, similar to findings elsewhere,11 39 40 probably affecting risk due to speed of travel and
resulting force of impact. While the overall topography of a city
is not modifiable, routes targeted for bicycle-specific infrastructure can be selected to minimise elevation changes to improve
safety and simultaneously reduce exertion from uphill travel.
Level surfaces and gentle slopes have been shown to be preferred by potential riders.5 The importance of grade to both
cycling safety and attractiveness highlights the opportunity to
foster cycling in naturally flat cities.
The current study used a case–crossover design10 that addresses
many of the challenges of observational studies of bicycle safety,13
including effective control for both exposure to risk and personal
factors that may affect both risk and environmental exposure such
as experience and risk aversion. The blinded observations and lack
of reliance on self-report of site characteristics offer advantages
over previously used methods.11 13 Cycling conditions were
observed after the injury event, so we cannot be sure they were
exactly as occurred on the injury trip. This should not affect stable
infrastructure such as route type, but may affect more transient
conditions, such as traffic counts. Because observations were made
in the identical way for injury and control sites, misclassification is
likely to be non-differential and to bias risk estimates to the null.
The most significant limitation of the current analysis was that
we could only examine the effects of infrastructure that was
present in the study cities, and not the full range of infrastructure
that could be used to mitigate cyclist risk. This calls for replication of our study in other cities with different types of infrastructure, and for further studies as new infrastructure is built.
The analyses reported here do not take the severity of the
injuries into account. A severity analysis is planned for the study
data, but the main focus of the study was the initial risk of being
involved in an injury crash, rather than the injury consequences.
The study was restricted to cyclists whose injuries were serious
enough to result in a visit to a hospital emergency department.
By using hospital records, injuries caused by all kinds of crashes
were included (eg, with a motor vehicle or not). We could not
include individuals who were so severely injured that that they
could not recall their trip route; however, few were excluded by
this eligibility criterion (two fatally injured and 26 who could not
remember their route). The results of this study therefore may
not apply to those with minor injuries not requiring emergency
treatment or with the most serious injuries.
We offered multiple variables to the models and some were
likely to be significant by chance alone. We have attempted to
be cautious in our interpretations, by looking for consistency
with other studies, and recommending verification in future
studies in which a result is novel. In addition, we have presented
complete tables showing all variables in the unadjusted and
adjusted models in supplementary tables (available online only)
for examination by interested readers.
CONCLUSIONS
Different infrastructure characteristics influenced risk at intersections and non-intersections. At intersections, significant variables were route types meeting at the intersection, intersection
type, cyclist travel direction, motor vehicle speed, cyclist traffic
count and route grade. At non-intersection locations, significant
variables were bike or pedestrian infrastructure, streetcar or
train tracks, construction and route grade. Only route grade was
significant in both analyses.
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Despite the differing variables important in the two analyses,
there are consistent patterns: features that separate cyclists from
motor vehicles and pedestrians (cycle tracks, local streets, traffic
diverters) and lower speeds (motor vehicle speeds less than
30 km/h, level grades) were associated with significantly lower
injury risk to cyclists. These features are incorporated into transportation design in northern European countries with high
cycling modal shares and low injury risk, and have been shown
to encourage cycling in North America.5 7–9 Important additional evidence from this study includes the importance of
obstacles in reducing safety (traffic circles, streetcar or train
tracks, construction). Transportation planners and engineers in
many North American cities are interested in promoting cycling
and will benefit from the accumulating evidence about the value
of building environments sensitive to cyclists.
What is already known on the subject
▸ The risk of injury associated with bicycling is higher in
North America than in northern European countries where
cycling infrastructure is common.
▸ Evidence is accumulating that routes with low motor vehicle
traffic and bicycle-specific infrastructure improve cycling safety.
▸ This evidence has been considered inconclusive because
previous studies have had unclear route definitions, grouped
routes with potentially different injury risks, and had poor
control for traffic volume and personal characteristics.
What this study adds
9
Departments of Surgery and Education and Public Health, University of Toronto,
Toronto, Ontario, Canada
10
Department of Pediatrics, University of British Columbia, Vancouver, British
Columbia, Canada
11
Department of Emergency Medicine, University of British Columbia, Vancouver,
British Columbia, Canada
12
Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
13
University Health Network, Toronto, Ontario, Canada
Acknowledgements The authors would like to thank all the study participants for
generously contributing their time. They appreciate the work of study staff, hospital
personnel and their city and community collaborators. This study evolved from work
conducted in the University of British Columbia’s Bridge Program Grant Development
course (2005–6) and benefited from input from the participants of that class.
Contributors KT, MAH, CCOR and PAC were responsible for initial conception and
design of the study. KT, MAH, CCOR, PAC, MW, SB, MLC, MDC, JRB, GH, SMF and
Kishore Mulpuri were responsible for the funding proposal. CCOR, MAH, MW, MM,
LV, MDC and KT designed and tested data collection instruments. MW, HS and KT
developed algorithms for defining route infrastructure. HS was responsible for data
analyses. All authors had full access to the results of all analyses. MAH, CCOR and
KT drafted the article. All authors contributed to study design and implementation,
analysis decisions, interpretation of results and critical revision of the article. Evan
Beaupré, Niki Blakely, Jill Dalton, Martin Kang, Kevin McCurley and Andrew Thomas
were responsible for interviews or site observations. Vartouji Jazmaji, MM and LV
were responsible for supervision and training of study staff, and recruitment of
participants. Barb Boychuk, Jan Buchanan, Doug Chisholm, Nada Elfeki, JRB, GH,
SMF and MDC contributed to the identification of injured cyclists at the study
hospitals. Jack Becker, Bonnie Fenton, David Hay, Nancy Smith Lea, Peter Stary, Fred
Sztabinski, David Tomlinson and Barbara Wentworth reviewed the study protocol,
data collection forms, infrastructure definitions and interpretation of results from the
perspective of professionals or advocates involved in cycling transportation. Data
were double entered by Express Data Ltd.
Funding This work was supported by a grant from the Heart and Stroke Foundation of
Canada and the Canadian Institutes of Health Research (Institute of Musculoskeletal
Health and Arthritis and Institute of Nutrition, Metabolism and Diabetes) (grant no
BEO-85863). JRB, MAH and MW were supported by salary awards from the Michael
Smith Foundation for Health Research. MAH, CCOR and MW were supported by salary
awards from the Canadian Institutes of Health Research.
Competing interests None.
▸ This study examined the injury risk associated with multiple
carefully defined and measured route infrastructure
characteristics. It analysed intersection and non-intersection
locations separately, to examine the special characteristics of
each. The case–crossover design effectively controlled for
personal, trip and exposure factors, allowing the focus to be on
route infrastructure.
▸ Intersections of two local streets had much lower risks than
intersections of two major streets, but traffic circles increased
the risk of these otherwise safe intersections. Entering
intersections in the direction opposite to traffic increased injury
risk, and motor vehicle speeds below 30 km/h reduced risk.
▸ At non-intersection locations, cycle tracks alongside major
streets but physically separated from traffic and local streets
with diverters that reduced motor vehicle traffic had much
lower injury risk than routes with no bike infrastructure.
Ethics approval A total of seven research ethics boards approved this protocol:
universities of Toronto and British Columbia and these hospitals: St Paul’s,
Vancouver General (Vancouver) and St Michael’s, Toronto General, Toronto Western
(Toronto).
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The study database was compiled from interviews with
study participants and site observations by study personnel. It cannot be shared by
the authors with anyone without approval from the university and hospital human
subjects review boards.
Open Access This is an Open Access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which
permits others to distribute, remix, adapt, build upon this work non-commercially,
and license their derivative works on different terms, provided the original work is
properly cited and the use is non-commercial. See: http://creativecommons.org/
licenses/by-nc/3.0/
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Comparing the effects of infrastructure on
bicycling injury at intersections and
non-intersections using a case−crossover
design
M Anne Harris, Conor C O Reynolds, Meghan Winters, Peter A Cripton,
Hui Shen, Mary L Chipman, Michael D Cusimano, Shelina Babul, Jeffrey
R Brubacher, Steven M Friedman, Garth Hunte, Melody Monro, Lee
Vernich and Kay Teschke
Inj Prev published online February 14, 2013
Updated information and services can be found at:
http://injuryprevention.bmj.com/content/early/2013/02/13/injuryprev2012-040561
These include:
Supplementary Supplementary material can be found at:
Material http://injuryprevention.bmj.com/content/suppl/2013/01/23/injuryprev2012-040561.DC1
References
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